• 한국멀티미디어학회논문지
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• 제19권1호
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• pp.68-79
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• 2016

Electromyographic (EMG) signals have been widely used as motion commands of prosthetic arms. Although EMG signals contain meaningful information including the movement intentions of human body, it is difficult to predict the subject's motion by analyzing EMG signals in real-time due to the difficulties in extracting motion information from the signals including a lot of noises inherently. In this paper, four Ag/AgCl electrodes are placed on the surface of the subject's major muscles which are in charge of four upper arm movements (wrist flexion, wrist extension, ulnar deviation, finger flexion) to measure EMG signals corresponding to the movements. The measured signals are sampled using DAQ module and clustered sequentially. The Fuzzy C-Means (FCMs) method calculates the center values of the clustered data group. The fuzzy system designed to detect the upper arm movement intention utilizing the center values as input signals shows about 90% success in classifying the movement intentions.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2011년도 추계학술대회
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• pp.279-280
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• 2011

In order to convert the mechanical movement of a linear generator to electrical power, the amateur current of the generator is controlled in accordance to the mover position. A linear encoder, usually used for direct detection of the mover position, not only is vulnerable to mechanical vibration, but also imposes significant constraint on the mechanical design of the generator system. Thus, this study proposes a method for indirect estimation of the mover position with emfs induced in amateur coils. The estimation algorithm is validated with simulation study.

• The Journal of Korean Physical Therapy
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• 제1권1호
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• pp.47-61
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• 1989

This paper presents the event approach to motor skill acquisition as a theoretical treatment of the learning and relearning of motor skill. 1) The use of norm-referenced developmental assesment tools and standardized qualitative assessment tool is an important component of infant movement evaluation. 2) The kinesthetic modality relaying movement and position imformation to the central nervous system is important for the detection and corretion of movement error. 3) The event approach treats the actor and the environment as inseparable in the acquisition of skills. 4) Motoy learning focuses almost entirely on how the skill is learned, contRolled and reTained. 5) Developmental assessment have needed an assessment of motor development. 6) A significant difference was found between articulation disorders children and motor coordination problem. 7) verbal ability is not essential for the learning of motor skills. 8) The Control of motor skills is a cognitive ability.

• 한국전자파학회논문지
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• 제11권2호
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• pp.228-233
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• 2000

본 논문에서는 무선광연결에서 끈사적 평균잡음검출을 이용한 차동검출방식에 대하여 소개한다 이 방식은 기존의 잠음광의 영향을 소거하는 차동검출기의 기능을 보완한다. 근사적 평균잡음전압을 이용하여 차동검출하면. 물체나 사람의 이동에 의하여 나타날 수 있는 잡음광 결합비의 순간적 변화에 의한 출력전압의 변동을 줄일 수 있다 이 것은 장음광의 공간적 분포가 수시로 변동하는 환경에서 무선광연결을 구성하는 경우 잡음광을 소거하는 데에 매우 효과적이다

• 전기전자학회논문지
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• 제24권4호
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• pp.1148-1155
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• 2020

Fire must be extinguished as quickly as possible because they cause a lot of economic loss and take away precious human lives. Especially, the detection of smoke, which tends to be found first in fire, is of great importance. Smoke detection based on image has many difficulties in algorithm research due to the irregular shape of smoke. In this study, we introduce a new real-time smoke detection algorithm that reduces the detection of false positives generated by irregular smoke shape based on faster r-cnn of factory-installed surveillance cameras. First, we compute the global frame similarity and mean squared error (MSE) to detect the movement of smoke from the input surveillance camera. Second, we use deep learning algorithm (Faster r-cnn) to extract deferred candidate regions. Third, the extracted candidate areas for acting are finally determined using space and temporal features as smoke area. In this study, we proposed a new algorithm using the space and temporal features of global and local frames, which are well-proposed object information, to reduce false positives based on deep learning techniques. The experimental results confirmed that the proposed algorithm has excellent performance by reducing false positives of about 99.0% while maintaining smoke detection performance.

• Smart Structures and Systems
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• 제22권5호
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• pp.561-574
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• 2018

In this paper, for efficiently reducing the computational cost of the model updating during the optimization process of damage detection, the structural response is evaluated using properly trained surrogate model. Furthermore, in practice uncertainties in the FE model parameters and modelling errors are inevitable. Hence, an efficient approach based on Monte Carlo simulation is proposed to take into account the effect of uncertainties in developing a surrogate model. The probability of damage existence (PDE) is calculated based on the probability density function of the existence of undamaged and damaged states. The current work builds a framework for Probability Based Damage Detection (PBDD) of structures based on the best combination of metaheuristic optimization algorithm and surrogate models. To reach this goal, three popular metamodeling techniques including Cascade Feed Forward Neural Network (CFNN), Least Square Support Vector Machines (LS-SVMs) and Kriging are constructed, trained and tested in order to inspect features and faults of each algorithm. Furthermore, three wellknown optimization algorithms including Ideal Gas Molecular Movement (IGMM), Particle Swarm Optimization (PSO) and Bat Algorithm (BA) are utilized and the comparative results are presented accordingly. Furthermore, efficient schemes are implemented on these algorithms to improve their performance in handling problems with a large number of variables. By considering various indices for measuring the accuracy and computational time of PBDD process, the results indicate that combination of LS-SVM surrogate model by IGMM optimization algorithm have better performance in predicting the of damage compared with other methods.

• 융합보안논문지
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• 제18권5_1호
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• pp.45-51
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• 2018

데이터의 활용도와 중요성이 점차 높아짐에 따라 데이터와 관련된 사고와 피해는 점점 증가 하고 있으며, 특히 내부자에 의한 사고는 그 위험성이 더 높다. 이런 내부자의 공격은 전통적인 보안 시스템으로 방어하기 힘들어, 규칙 기반의 이상 행동 탐지 방법이 널리 활용되어오고 있다. 하지만, 새로운 공격 방식 및 새로운 환경과 같이 변화에 유연하게 적응하지 못하는 문제점을 가지고 있다. 본 논문에서는 이에 대한 해결책으로서 통계적 마르코프 모델 기반의 적응형 이상 이동 탐지 프레임워크를 제안하고자 한다. 이 프레임워크는 사람의 이동에 초점을 맞추어 내부자에 의한 위험을 사전에 탐지한다. 이동에 직접적으로 영향을 주는 환경 요소와 지속적인 통계 학습을 통해 변화하는 환경에 적응함으로써 오탐지와 미탐지를 최소화하도록 설계되었다. 프레임워크를 활용한 실험에서는 0.92의 높은 F2-점수를 얻을 수 있었으며, 나아가 정상으로 보여지지만, 의심해볼 이동까지 발견할 수 있었다. 통계 학습과 환경 요소를 바탕으로 행동과 관련된 데이터와 모델링 알고리즘을 다양화 시켜 적용한다면 보다 더 범위 넓은 비정상 행위에 대해 탐지할 수 있는 확장성을 제공한다.

• 대한전자공학회논문지SP
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• 제45권2호
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• pp.49-64
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• 2008

최근에 휴먼 컴퓨터 인터페이스 분야에서 사용자의 시선 위치를 파악하여 더욱 편리한 입력장치를 구축하고자 하는 연구가 많이 진행되고 있다. 하지만 복잡한 하드웨어 구성으로 제품의 가격이 매우 비싸고, 까다로운 사용자 캘리브레이션 과정으로 인해 시스템의 사용에 어려움을 겪는다. 본 논문에서는 HMD(Head Mounted Display)에 USB 카메라와 적외선을 반사시키는 hot-mirror와 적외선 조명을 이용한 시선 추적 모듈을 부착하고, 이를 통해 획득한 눈 영상의 2차원적인 분석과 간단한 사용자 캘리브레이션 과정을 통해 시선 위치를 파악하는 방법을 제안한다. HMD는 사용자의 얼굴 움직임과 함께 움직이므로, 얼굴움직임에 영향을 받지 않는 시선 추적 시스템을 구현할 수 있다. 또한, 시선 추적 시스템을 3차원 1인칭 슈팅 게임에 적응하여, 캐릭터의 시선 방향을 조정하고, 적 캐릭터를 조준하여 사격이 가능하도록 하여, 게임의 몰입감과 흥미성을 높일 수 있게 하였다. 실험 결과, 한 대의 데스크톱 컴퓨터 환경에서 게임과 시선 추적 시스템이 실시간으로 동작 가능했으며, 약 $0.88^{\circ}$의 시선 위치 추출 오차를 보였다. 또한 3차원 1인칭 슈팅게임에서 일반 마우스의 역할을 시선 추적 시스템이 문제없이 대신할 수 있음을 확인하였다.

• 대한의용생체공학회:학술대회논문집
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• 대한의용생체공학회 1998년도 추계학술대회
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• pp.201-202
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• 1998

In this paper we suggested an automated method for detecting and counting rapid eye movement(REM) using EOG during sleep. This method is formulated by two step fuzzy logic. At first step, the velocity and the distance of single channel eye movement are used for the fuzzy input to get the possibility of being REM at each EOG. At second step, the two possibility values of both EOG from the first step and the correlation coefficient of both eye movements are used for the fuzzy logic input, and the output is the final possibility of being Rapid Eye Movement. We applied this algorithm to the normal and narcoleptic sleep data and compared the difference. We found the possibility that the count of REM can be a parameter that has significant physiological meanings.

• 수산해양기술연구
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• 제46권3호
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• pp.232-238
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• 2010

The moving ranges and behavior of four wild abalones, Haliotis discus hannai, were measured by an acoustic telemetry technique. The shape of the sea bottom of the experimental area was surveyed by a bathymetry system and three self-recording type acoustic receivers were used for monitoring the behavior and measuring the movement range. The abalones (WA1-WA4) attached acoustic tags were released and measured the movement during ten months. Three abalones (WA1, WA3 and WA4) were successively detected around the released point during the experiment and were moved to the V2 area where water depth is deeper than the V1 area. The change of inhabitation depth was also detected from the depth sensor of WA4. As the result, abalones were moved to deeper water area accordance with the decrease of the water temperature. The moved ranges of abalones were approximately 200 - 400m from the release point.